Background: The data revolution in education has led to more data collection, more randomized controlled trials (RCTs), and more data collection within RCTs. Often following IES recommendations, researchers studying program effectiveness gather data on how the intervention was implemented. Educational implementation data can be complex, including…

Randomized experiments involving education interventions are typically implemented as cluster randomized trials, with schools serving as clusters. To design such a study, it is critical to understand the degree to which learning outcomes vary between versus within clusters (schools), specifically the intraclass correlation coefficient. It is also…

The importance of learning design in education is widely acknowledged in the literature. Should learners make effective use of opportunities provided in a learning design, especially in online environments, previous studies have shown that they need to have strong skills for self-regulated learning (SRL). The literature, which reports the use of…

Consistency of learning behaviors is known to play an important role in learners' engagement in a course and impact their learning outcomes. Despite significant advances in the area of learning analytics (LA) in measuring various self-regulated learning behaviors, using LA to measure consistency of online course engagement patterns remains largely…

This paper presents an approach to information literacy instruction in colleges and universities that combines online and classroom learning (Blended Learning). The concept includes only one classroom seminar, so the approach presented here can replace existing one-shot sessions at colleges and universities without changes to the current workflow.…

Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…

This article presents "concept landscapes"--a novel way of investigating the state and development of knowledge structures in groups of persons using concept maps. Instead of focusing on the assessment and evaluation of single maps, the data of many persons is aggregated and data mining approaches are used in analysis. New insights into…

Background: This study aimed to examine whether verbal responsiveness in special education teachers varied among subgroups of children with autism spectrum disorder (n = 112) who differed in cognitive and language abilities. Methods: Participants were divided into clusters using cluster analysis based on standardised cognitive and language tests…

Concept maps have a long history in educational settings as a tool for teaching, learning, and assessing. As an assessment tool, they are predominantly used to extract the structural configuration of learners' knowledge. This article presents an investigation of the knowledge structures of a large group of beginning CS students. The investigation…

In recent years there has been a proliferation of massive open online courses (MOOCs), which provide unprecedented opportunities for lifelong learning. Registrants approach these courses with a variety of motivations for participation. Characterizing the different types of participation in MOOCs is fundamental in order to be able to better…

In this paper, we describe multimodal learning analytics (MMLA) techniques to analyze data collected around an interactive learning environment. In a previous study (Schneider & Blikstein, submitted), we designed and evaluated a Tangible User Interface (TUI) where dyads of students were asked to learn about the human hearing system by…

Massive open online courses (MOOCs) are being used across the world to provide millions of learners with access to education. Many who begin these courses complete them successfully, or to their own satisfaction, but the high numbers who do not finish remain a subject of concern. In 2013, a team from Stanford University analyzed engagement…

Feedback is known to have a large influence on student learning gains, and the emergence of online tools has greatly enhanced the opportunity for delivering timely, expressive, digital feedback and for investigating its learning impacts. However, to date there have been no large quantitative investigations of the feedback provided by large teams…

The use of analytic methods for extracting learning strategies from trace data has attracted considerable attention in the literature. However, there is a paucity of research examining any association between learning strategies extracted from trace data and responses to well-established self-report instruments and performance scores. This paper…

In this study, we follow students' modeling and covariational reasoning in the context of learning about big data. A three-week unit was designed to allow 12th grade students in a mathematics course to explore big and mid-size data using concepts such as trend and scatter to describe the relationships between variables in multivariate settings.…